Christina Triantafyllou1, Jonathan R Polimeni2, Boris Keil2, Lawrence L Wald2,3. 1. Siemens Healthcare GmbH, Erlangen, Germany. 2. Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, Massachusetts, USA. 3. Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Abstract
PURPOSE: Physiological nuisance fluctuations ("physiological noise") are a major contribution to the time-series signal-to-noise ratio (tSNR) of functional imaging. While thermal noise correlations between array coil elements have a well-characterized effect on the image Signal to Noise Ratio (SNR0 ), the element-to-element covariance matrix of the time-series fluctuations has not yet been analyzed. We examine this effect with a goal of ultimately improving the combination of multichannel array data. THEORY AND METHODS: We extend the theoretical relationship between tSNR and SNR0 to include a time-series noise covariance matrix Ψt , distinct from the thermal noise covariance matrix Ψ0 , and compare its structure to Ψ0 and the signal coupling matrix SSH formed from the signal intensity vectors S. RESULTS: Inclusion of the measured time-series noise covariance matrix into the model relating tSNR and SNR0 improves the fit of experimental multichannel data and is shown to be distinct from Ψ0 or SSH . CONCLUSION: Time-series noise covariances in array coils are found to differ from Ψ0 and more surprisingly, from the signal coupling matrix SSH . Correct characterization of the time-series noise has implications for the analysis of time-series data and for improving the coil element combination process. Magn Reson Med 76:1708-1719, 2016.
PURPOSE: Physiological nuisance fluctuations ("physiological noise") are a major contribution to the time-series signal-to-noise ratio (tSNR) of functional imaging. While thermal noise correlations between array coil elements have a well-characterized effect on the image Signal to Noise Ratio (SNR0 ), the element-to-element covariance matrix of the time-series fluctuations has not yet been analyzed. We examine this effect with a goal of ultimately improving the combination of multichannel array data. THEORY AND METHODS: We extend the theoretical relationship between tSNR and SNR0 to include a time-series noise covariance matrix Ψt , distinct from the thermal noise covariance matrix Ψ0 , and compare its structure to Ψ0 and the signal coupling matrix SSH formed from the signal intensity vectors S. RESULTS: Inclusion of the measured time-series noise covariance matrix into the model relating tSNR and SNR0 improves the fit of experimental multichannel data and is shown to be distinct from Ψ0 or SSH . CONCLUSION: Time-series noise covariances in array coils are found to differ from Ψ0 and more surprisingly, from the signal coupling matrix SSH . Correct characterization of the time-series noise has implications for the analysis of time-series data and for improving the coil element combination process. Magn Reson Med 76:1708-1719, 2016.
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